Arbitration is a key non-litigation commercial mechanism for the resolution of disputes, and the quality and credibility of its awards depend largely on the competency of the arbitrators. However, the selection and ev...Arbitration is a key non-litigation commercial mechanism for the resolution of disputes, and the quality and credibility of its awards depend largely on the competency of the arbitrators. However, the selection and evaluation systems for arbitrators in China have long faced challenges such as the vague criteria for competency and an unclear professionalization path for arbitrators. To address these issues, this study is grounded in the context of actual Chinese arbitration practice and based on the competency iceberg model. Through a methodological approach encompassing literature reviews, behavioral event interviews, expert revisions, and questionnaire surveys, a Chinese Arbitrator Competency Scale was developed and validated in this study. Examination of the findings indicated that the scale needed to consist of five dimensions—communication and coordination, cognitive skills, ethical conduct, work motivation, and personality traits—and possess a total of 28 specific indicators. Confirmatory analysis of the factors demonstrates a good fit for the five-dimensional model, with each of the dimensions exhibiting high reliability and validity. This scale is innovative in integrating the competency elements with Chinese characteristics, such as commercial acumen, crosscultural mediation skills, and adaptability to the local rule of law. This research not only enriches the competency theory in regard to the field of human resource management but also provides a scientific framework of standards and measurement tools for the selection, training, and evaluation of arbitrators. It thus has significant practical value for enhancing the professionalism and international competitiveness of China's arbitration system.展开更多
Practical activities are an indispensable piece of science education.As such,assessment of these practical activities is vital for continually enhancing the quality of science instruction.This article presents a tenta...Practical activities are an indispensable piece of science education.As such,assessment of these practical activities is vital for continually enhancing the quality of science instruction.This article presents a tentative framework structured for assessing practical activities in science education.The proposed framework is built upon seven components:engagement and participation,relational thinking,stepwise mastery,contextualization,multidimensional integration,empowerment,and scientific articulacy.The framework might provide science educators with an alternative lens through which to enhance the effectiveness of practical activities,promote student engagement,and better prepare learners for the future.This framework is designed to be additive and complementary to existing assessment approaches and can be adapted and customized to suit specific local contexts and varying grade levels by science educators in the pursuit of excellence in an ever-evolving science education landscape.展开更多
The NIST Cybersecurity Framework (NIST CSF) serves as a voluntary guideline aimed at helping organizations, tiny and medium-sized enterprises (SMEs), and critical infrastructure operators, effectively manage cyber ris...The NIST Cybersecurity Framework (NIST CSF) serves as a voluntary guideline aimed at helping organizations, tiny and medium-sized enterprises (SMEs), and critical infrastructure operators, effectively manage cyber risks. Although comprehensive, the complexity of the NIST CSF can be overwhelming, especially for those lacking extensive cybersecurity resources. Current implementation tools often cater to larger companies, neglecting the specific needs of SMEs, which can be vulnerable to cyber threats. To address this gap, our research proposes a user-friendly, open-source web platform designed to simplify the implementation of the NIST CSF. This platform enables organizations to assess their risk exposure and continuously monitor their cybersecurity maturity through tailored recommendations based on their unique profiles. Our methodology includes a literature review of existing tools and standards, followed by a description of the platform’s design and architecture. Initial tests with SMEs in Burkina Faso reveal a concerning cybersecurity maturity level, indicating the urgent need for improved strategies based on our findings. By offering an intuitive interface and cross-platform accessibility, this solution aims to empower organizations to enhance their cybersecurity resilience in an evolving threat landscape. The article concludes with discussions on the practical implications and future enhancements of the tool.展开更多
Overall bank performance in a particular year or period is important to all banking industry stakeholders,as it indicates their success or failure relative to predetermined targets.Due to conflicting criteria and unce...Overall bank performance in a particular year or period is important to all banking industry stakeholders,as it indicates their success or failure relative to predetermined targets.Due to conflicting criteria and uncertainties,assessing bank performance is a complicated decision-making problem.The current paper proposes the Fuzzy Level Based Weight Assessment(F-LBWA),the Fuzzy Logarithm Methodology of Additive Weights(F-LMAW),and the Measurement Alternatives and Ranking according to the Compromise Solution(MARCOS)combination as a practical and robust decisionmaking tool to cope with many complex ambiguities.In the first phase,the suggested hybrid Multi-Criteria Decision-Making(MCDM)approach estimates the weight coefficients of the performance criteria with the aid of a combined version of the F-LBWA and F-LMAW methods.In the second phase,the MARCOS method determines the ranking performance of the decision alternatives.The introduced model is tested and validated on a case study assessing publicly traded bank performance in Pakistan.The findings obtained from the sensitivity analysis revealed that the presented F-LBWAF-LMAW-MARCOS approach produces consistent solutions and is a reliable and effective procedure in rational decision-making.展开更多
Proficiency in fundamental movement skills in children is linked to numerous positive physical,behavioral,and cognitive outcomes.The Test of Gross Motor Development is a widely used tool in research to measure this ou...Proficiency in fundamental movement skills in children is linked to numerous positive physical,behavioral,and cognitive outcomes.The Test of Gross Motor Development is a widely used tool in research to measure this outcome.However,its application faces several limitations and challenges,such as subjectivity in rater judgements,limitation in data precision,and inconsistencies in score aggregations.In this commentary,we discuss these issues and explore how new technology might help address some of the challenges.Nonetheless,a consensus to how scores should be aggregated is still needed,and this could only be achieved through further discussions among researchers in the field.展开更多
Before nationwide implementation of waste classification programs in rural areas,identifying suitable pilot regions is crucial.This study develops a comprehensive framework for assessing and selecting these pilot regi...Before nationwide implementation of waste classification programs in rural areas,identifying suitable pilot regions is crucial.This study develops a comprehensive framework for assessing and selecting these pilot regions.Data were collected through 654 valid questionnaires and interviews with respondents from rural areas in six provinces across China.Primary assessment criteria included disposal methods for kitchen waste,recyclables,hazardous waste,and residual waste,as well as farmers’willingness to separate hazardous waste when offered compensation and the impact of centralized waste treatment in villages.Secondary criteria focused on disposal methods for agrochemical packages and other hazardous waste.Using the weighted sum of squares method,the study evaluated the suitability of six regions as pilot areas for waste classification.The results identified villages in Jiangsu province and Hebei province as the most suitable pilot regions.Based on the findings,the study provides recommendations to address weaknesses in these regions to enhance the effectiveness of future trials and offers tailored suggestions for other regions to improve their waste classification initiatives.展开更多
The increasing frequency and intensity of forest fires,driven by climate change and human activities,pose a significant threat to vital forest ecosystems,particularly where fire is not a natural element in the regener...The increasing frequency and intensity of forest fires,driven by climate change and human activities,pose a significant threat to vital forest ecosystems,particularly where fire is not a natural element in the regeneration cycle.This study aims to identify the indicators influencing forest fire vulnerability and compare maps of forest fire susceptibility that are based on the Intergovernmental Panel on Climate Change tripartite model,with a focus on the vulnerable Hyrcanian forest region in Golestan Province,northern Iran,where forest fires have caused considerable economic losses.On the basis of expert opinions and a literature review,we used geographic information systems,remote sensing and machine learning techniques to select and weigh 30 biophysical,environmental and socioeconomic indicators that affect forest fire vulnerability in the study area.These indicators were rigorously normalized,weighted and amalgamated into a comprehensive forest fire vulnerability index to analyze forest exposure,sensitivity and adaptive capacity.We thus identified and mapped areas with very high forest fire exposure,high sensitivity and low adaptive capacity for urgent targeted intervention and strategic planning to mitigate the impacts of forest fires.The results also revealed a set of critical indicators that contribute more significantly to forest fire vulnerability(e.g.,precipitation,elevation and factors related to biodiversity,human activity and economic reliance on forest resources).Our results provide insights that can inform policy-making,community engagement and environmental management strategies to mitigate the vulnerabilities associated with forest fires in the Hyrcanian forest.展开更多
Assessing the vulnerability of a platform is crucial in its design.In fact,the results obtained from vulnerability analyses provide valuable information,leading to precise design choices or corrective solutions that e...Assessing the vulnerability of a platform is crucial in its design.In fact,the results obtained from vulnerability analyses provide valuable information,leading to precise design choices or corrective solutions that enhance the platform's chances of surviving different scenarios.Such scenarios can involve various types of threats that can affect the platform's survivability.Among such,blast waves impacting the platform's structure represent critical conditions that have not yet been studied in detail.That is,frameworks for vulnerability assessment that can deal with blast loading have not been presented yet.In this context,this work presents a fast-running engineering tool that can quantify the risk that a structure fails when it is subjected to blast loading from the detonation of high explosive-driven threats detonating at various distances from the structure itself.The tool has been implemented in an in-house software that calculates vulnerability to various impacting objects,and its capabilities have been shown through a simplified,yet realistic,case study.The novelty of this research lies in the development of an integrated computational environment capable of calculating the platform's vulnerability to blast waves,without the need for running expensive finite element simulations.In fact,the proposed tool is fully based on analytical models integrated with a probabilistic approach for vulnerability calculation.展开更多
This study aims to assess seismic hazards and develop effective mitigation strategies for the Mentawai-Siberut region in Indonesia.The research uses quantitative and qualitative methods to analyze historical seismic d...This study aims to assess seismic hazards and develop effective mitigation strategies for the Mentawai-Siberut region in Indonesia.The research uses quantitative and qualitative methods to analyze historical seismic data,predictive models,and stakeholder perspectives.The quantitative analysis includes seismic hazard estimation using the Gutenberg-Richter formula,ground movement analysis based on GMPE,and time interval calculations to forecast future earthquakes.Qualitative methods involve Policy Network Theory to explore the roles and interactions of various stakeholders in disaster management,including government agencies,Indonesian Archipelago Youth Association(NGOs),local communities,and academic researchers.Findings reveal significant seismic activity in the area,with historical earthquakes of magnitudes 8 and 9 occurring at intervals of 18 to 232 years.Predictions suggest a potential magnitude 8 earthquake around 2083,with a megathrust event likely around 2123.The study also identifies economic costs and losses,with damage from a megathrust estimated between USD 1.5–2.5 billion and 10-20 billion,including destroyed homes and displaced populations.Challenges include infrastructure limitations,logistical constraints,and enhancing disaster preparedness and response.The study emphasizes the importance of improving infrastructure,strengthening disaster preparedness,and updating early warning systems.Effective collaboration among stakeholders and integrating local knowledge into disaster management strategies are crucial for enhancing regional resilience.Recommendations include completing infrastructure projects like the Trans-Mentawai Road,increasing community engagement,and utilizing scientific data for evidence-based policymaking.Addressing these recommendations and limitations is essential for developing a robust disaster management framework to mitigate regional seismic risks.展开更多
Changes in lake levels, as an indicator of climate change, are crucial for understanding water resources.Satellite altimetry has proven to be an effective technique for monitoring water level changes in inland lakes. ...Changes in lake levels, as an indicator of climate change, are crucial for understanding water resources.Satellite altimetry has proven to be an effective technique for monitoring water level changes in inland lakes. However, high-altitude and high-latitude lakes undergo seasonal freezing and melting, affecting satellite altimetry accuracy. This paper evaluates the accuracy of lake level height observations by the CryoSat-2, which uses synthetic aperture radar(SAR) across seasons. First, we used lake boundary based on optical remote sensing data to extract the footprints of CryoSat-2 that fall on Namco and Zhari Namco.After elevation conversion and anomaly identification, we obtained the time series of lake levels. These data were compared and verified against lake levels from in-situ measurements to assess the accuracy of CryoSat-2. The results show that CryoSat-2 can monitor lake level height with an accuracy of about 10-13 cm. The correlation coefficient between CryoSat-2 observations and in-situ measurements over Namco is 0.80(p < 0.01), with a Root Mean Square Error(RMSE) of 13 cm. For Zhari Namco, the correlation coefficient is 0.91, with an RMSE of 10 cm, indicating a better match. At the seasonal scale, the seasonal correlation coefficients between CryoSat-2 and in-situ measurement in Namco are 0.47(spring),0.79(summer), and 0.91(fall) with no observations available for winter. The lower correlation in spring may be due to incomplete ice melting. For Zhari Namco, the seasonal correlation coefficients are 0.89(spring), 0.93(summer), 0.89(fall), and 0.87(winter). The results show that CryoSat-2 accuracy is higher in summer and fall, while slightly lower in spring and winter, indicating that ice formation affects accuracy. Even during winter, the altimetry results do not significantly exceed the in-situ lake water level observations.展开更多
Background:In this study,we aimed to validate and test the reliability of the Yonsei lifestyle profile(YLP)in assessing multifaceted health lifestyle levels in a study population from the United States.Methods:The YLP...Background:In this study,we aimed to validate and test the reliability of the Yonsei lifestyle profile(YLP)in assessing multifaceted health lifestyle levels in a study population from the United States.Methods:The YLP-English version and health-promoting lifestyle profile II were administered to 100 individuals living in the United States.Concurrent validity was analyzed using Pearson's correlation coefficient,and discriminant validity was examined by comparing sex and age differences through t-tests and multiple variance analysis.Internal consistency was assessed using Cronbach'sαfor each sub-factor.Results:The YLP-English Version demonstrated concurrent validity with the Health-Promoting Lifestyle Profile II,showing consistent correlations for the total score(0.3,p<0.01)and frequency sub-factors(0.25-0.69,p<0.01).Among the satisfaction sub-factors,only nutrition showed a weak negative correlation(-0.19,p<0.01);all others were nonsignificant.Discriminant validity revealed no significant sex differences,but physical activity frequency varied across age groups.Internal consistency was high(Cronbach'sα=0.80-0.86).Conclusion:In this study,we validated the YLP-English version as a reliable instrument for assessing health-related lifestyle behaviors.The YLP uniquely captures both lifestyle frequency and satisfaction,offering a comprehensive perspective on health behaviors.Although this tool is currently most applicable in population-level studies,future research should establish clinical thresholds to enhance its utility in individualized health assessments and interventions.展开更多
The concentration of development projects near protected areas can undermine their conservation objectives.This study examines the impact of such projects on wildlife abundance in Campo-Ma’an National Park(CMNP).Info...The concentration of development projects near protected areas can undermine their conservation objectives.This study examines the impact of such projects on wildlife abundance in Campo-Ma’an National Park(CMNP).Information from the CMNP Conservation Department was analysed to investigate the link between development projects around the park and changes in wildlife populations,and analysis was conducted using statistical tools,including Excel 2020 and SPSS.Pearson’s correlation coefficient was employed to assess the relationship between wildlife abundance indicators and the number of development projects surrounding the park.The findings reveal a significant decline in the abundance of key species,including elephants,great apes(such as gorillas and chimpanzees),and mandrills,over the past decade.Although a brief period of improvement was observed in the early 2010s,these gains were quickly reversed.Overall,the pattern shows that as development activities increased,wildlife numbers tended to decrease.These results underscore the urgent need for stricter regulation of development near the park and for comprehensive environmental and social impact assessments to be conducted before projects commencement.This process must receive greater attention from authorities and stakeholders to regulate activities around national parks and foster conservation efforts.Strengthening this oversight will help to maintain the park’s ecological integrity and promote sustainable conservation.展开更多
Chemical exposure during prenatal development has significant implications for both maternal and child health.Compared to blood,saliva is a non-invasive and less resource-intensive,alternative.Given the temporal varia...Chemical exposure during prenatal development has significant implications for both maternal and child health.Compared to blood,saliva is a non-invasive and less resource-intensive,alternative.Given the temporal variability of xenobiotic metabolites(XM),repeated sampling is essential.Therefore,saliva offers a valuable tool for the longitudinal assessment of prenatal exposomes.Despite its potential,no studies have explored saliva for XM measurement.This study pioneered using saliva to assess XM detectability and investigate the associations between prenatal XM and endogenous metabolomes in pregnant women.Saliva samples were analysed using mass spectrometry from 80 pregnant women at 24–34 weeks gestation.Metabolomes and exposomes were annotated using the Human Metabolome and U.S.Environmental Protection Agency databases.Metabolome-XM associations were clustered using Glay community clustering.Linear regression models,adjusted for age,estimated associations between catecholamines and XMs.XM levels were validated in a cohort of women(n=14)with and without preeclampsia.Our study identified 582 metabolomes and 125 XM in saliva,demonstrating its potential as a matrix for exposure measurement.After false discovery rate correction,18109 significant metabolome-XM associations were identified.Community clustering revealed 37 connected clusters,with the largest cluster(238 nodes)enriched in tyrosine and catecholamine metabolism.Food-contactchemicals and food-additives were significantly associated with higher catecholamine and their metabolite levels.Subgroup analyses revealed higher concentrations of these chemicals in women with preeclampsia compared to healthy controls.This study demonstrates that saliva contains valuable molecular data for measuring exposomes.Food-related chemicals were associated with higher catecholamine levels,which may be relevant to the prevalence of hypertensive crises in pregnancy.展开更多
Chronic diseases,or NCDs(noncommunicable diseases),constitute a major global health challenge,causing millions of deaths and imposing substantial economic burdens annually.This paper introduces the Health Score,a comp...Chronic diseases,or NCDs(noncommunicable diseases),constitute a major global health challenge,causing millions of deaths and imposing substantial economic burdens annually.This paper introduces the Health Score,a comprehensive framework for assessing chronic disease risk by integrating diverse determinants of health,including social,economic,environmental,behavioral,treatment,culture,and nature factors.The Health Score,ranging from 0 to 850,quantifies indivi dual and population-level health risks while identifying protective factors through a structured methodology that supports targeted interventions at individual,corporate,and community scales.The paper highlights the rising prevalence of chronic diseases in the United States,projecting that nearly half of the population will be affected by 2030,alongside a global economic burden expected to reach trillions of dollars.Existing surveillance tools,such as the CDS(Chronic Disease Score)and CDIs(Chronic Disease Indicators),are examined for their roles in monitoring health disparities.The Health Score advances a holistic,proactive approach,emphasizing lifestyle modifications,equitable healthcare access,economic opportunities,social support,nature exposure,cu ltural awareness,and community engagement.By elucidating the complex interplay of health determinants,this framework equips stakeholders with actionable insights to implement effective prevention strategies,ultimately fostering healthier,more resi lient populations.展开更多
Excessive fossil fuel use has increased carbon dioxide(CO_(2)) emissions,driving climate change and ocean acidification.This review evaluates the potential of higher alcohols as fuels for carbon circularity,comparing ...Excessive fossil fuel use has increased carbon dioxide(CO_(2)) emissions,driving climate change and ocean acidification.This review evaluates the potential of higher alcohols as fuels for carbon circularity,comparing their properties,energy efficiency,and technology readiness with hydrogen,methane,and methanol.Higher alcohols,produced via CO_(2) hydrogenation,exhibit advantages such as liquid-phase storage,higher energy density,and safer handling.Additionally,their clean combustion produces fewer pollutants like CO and NO_(x).However,CO_(2) hydrogenation to higher alcohols faces challenges,including high energy demands,kinetic barriers,and immature production technologies,resulting in lower energy efficiency compared to H_(2),methane,and methanol.Higher alcohols,with their superior energy density and safety,hold promise as sustainable fuels,particularly when integrated with CO_(2) capture technologies.However,improvements in catalyst performance,process integration,and production scalability are critical for their widespread adoption.展开更多
Rapid developments in the electronic information industry drive the increased energy usage and carbon emission of data center buildings,prompting the focus on the energy efficiency and environmental sustainability.Exp...Rapid developments in the electronic information industry drive the increased energy usage and carbon emission of data center buildings,prompting the focus on the energy efficiency and environmental sustainability.Expanded operation envelopes of tropical data centers is assessed to analyze the potential for the building energy savings and carbon emission reduction through collaborative analysis of operation modes(OMs),supply air temperature(SAT),and outdoor air temperature(OAT).The OMs of compression vary with the setpoints of SAT,in which the average exergy efficiency of compressors at alternate operation mode is 6.8%and 8.0%lower than that of double and single compression operations.As SAT rises from 20℃to 32℃,the system exergoeconomic factor increases from 5.4%to 8.0%,and the average carbon cost decreases by 36.5%.Additionally,with just an 8.5%increase in exergy cost(i.e.,Case 8)at OAT rising from 30 to 34℃,the high SAT and low refrigerant charges provide considerable exergy cost advantages versus resisting the OAT fluctuations.Dynamic operation strategies are also proposed and compared to cope with the impacts of tropical environments.Compared to the 26℃SAT baseline,the average energy savings are 9.1-14.7%,indicating the ability to fully utilize outdoor and indoor conditions.展开更多
The assessment of landslide susceptibility triggered by earthquakes serves as a fundamental basis for effective emergency response and post-disaster reconstruction efforts.However,current predictive models often face ...The assessment of landslide susceptibility triggered by earthquakes serves as a fundamental basis for effective emergency response and post-disaster reconstruction efforts.However,current predictive models often face limitations in accuracy,with the prediction rates of most models ranging from 80%to 90%.This study introduces a new hybrid machine learning framework,termed the Subtractive Clustering Method-based Adaptive Neural Network Fuzzy Inference System(SCM-ANFIS),and evaluates its performance in the Wenchuan earthquake region.This region features distinctive geology(e.g.,Longmenshan Fault-governed complex tectonics)and abundant fundamental data;additionally,the 2008 Wenchuan Earthquake provides a pertinent case for earthquakeinduced landslide model evaluation.Based on a literature review and correlation analysis,this study systematically identified 12 key influencing factors that collectively characterize the region's high landslide susceptibility,shaped by intense seismic activity,complex terrain,and fragmented rock masses.Positive and negative samples were extracted as target variables through buffer sampling to calculate earthquake-induced landslide susceptibility.The susceptibility zoning map was then calibrated and generated by incorporating the regional landslide area percentage.The study concludes the following:(1)Compared to traditional machine learning approaches,the model demonstrates strong performance and stability,achieving a prediction accuracy of 98.5%.Approximately 97.89%of historically documented landslides in the Wenchuan region were located within areas identified as having high susceptibility,which aligns well with observed spatial distributions.(2)Increase in the buffer distance contributes to enhance prediction accuracy while a larger sample size improves model stability.(3)The model exhibits superior performance and possesses scalability for application in other regions,such as Jiuzhaigou and Luding.(4)Nonetheless,limitations remain regarding uncertainty,sample composition,algorithmic design,and practical implementation.Future research should focus on improving data precision and optimizing algorithmic frameworks.Overall,this study provides valuable support for landslide susceptibility assessments and contributes essential data for disaster risk mitigation efforts.展开更多
Eco-driving behaviors have been recommended around the world because the transport is a key factor of energy use and pollution emissions.Therefore,based on the driving decision model,this paper introduces three aspect...Eco-driving behaviors have been recommended around the world because the transport is a key factor of energy use and pollution emissions.Therefore,based on the driving decision model,this paper introduces three aspects of the driving decisions(strategic decision,tactical decision and operation decision)to analyze the economy of vehicle energy.The analytic hierarchy process(AHP)is used to assign the weight of the internal evaluation indexes,so as to form a complete assessment for drivers'eco-driving behaviors.The research result can not only quantitatively describe the energy-saving effect of drivers'decisions,but also put forward targeted driving suggestions to optimize drivers'eco-driving behaviors.This assessment model helps to clarify the potential of eco-driving on energy economy of transportation in a hierarchical way,and provides a valuable theoretical basis for the further promotion and application of eco-driving education.展开更多
With the expanding applications of unmanned aerial vehicles(UAVs),precise flight evaluation has emerged as a critical enabler for efficient path planning,directly impacting operational performance and safety.Tradition...With the expanding applications of unmanned aerial vehicles(UAVs),precise flight evaluation has emerged as a critical enabler for efficient path planning,directly impacting operational performance and safety.Traditional path planning algorithms typically combine Dubins curves with local optimization to minimize trajectory length under 3D spatial constraints.However,these methods often overlook the correlation between pilot control quality and UAV flight dynamics,limiting their adaptability in complex scenarios.In this paper,we propose an intelligent flight evaluation model specifically designed to enhancemulti-waypoint trajectory optimization algorithms.Our model leverages a decision tree to integrate attitude parameters and trajectory matching metrics,establishing a quantitative link between pilot control quality and UAV flight states.Experimental results demonstrate that the proposed model not only accurately assesses pilot performance across diverse skill levels but also improves the optimality of generated trajectories.When integrated with our path planning algorithm,it efficiently produces optimal trajectories while strictly adhering to UAV flight constraints.This integrated framework highlights significant potential for real-time UAV training,performance assessment,and adaptive mission planning applications.展开更多
Dear Editor,On July 25,2024,an Oncologic Drugs Advisory Committee meeting was held to discuss the design of the AEGEAN trial,which evaluated the perioperative use of durvalumab for resectable non-small cell lung cance...Dear Editor,On July 25,2024,an Oncologic Drugs Advisory Committee meeting was held to discuss the design of the AEGEAN trial,which evaluated the perioperative use of durvalumab for resectable non-small cell lung cancer(NSCLC)[1].The Food and Drug Administration(FDA)stated that the two-arm trial was not designed to isolate contributions of neoadjuvant and adjuvant phases.Since the clinical benefit of adjuvant durvalumab remains uncertain,this limitation raises concerns about potential over-treatment.展开更多
基金Research on Problems and Countermeasures in Building the Capacity of the Grassroots International Chambers of Commerce in the Context of High-Quality Development (W2024H03841)a key research project of the China Council for the Promotion of International Trade in 2025。
文摘Arbitration is a key non-litigation commercial mechanism for the resolution of disputes, and the quality and credibility of its awards depend largely on the competency of the arbitrators. However, the selection and evaluation systems for arbitrators in China have long faced challenges such as the vague criteria for competency and an unclear professionalization path for arbitrators. To address these issues, this study is grounded in the context of actual Chinese arbitration practice and based on the competency iceberg model. Through a methodological approach encompassing literature reviews, behavioral event interviews, expert revisions, and questionnaire surveys, a Chinese Arbitrator Competency Scale was developed and validated in this study. Examination of the findings indicated that the scale needed to consist of five dimensions—communication and coordination, cognitive skills, ethical conduct, work motivation, and personality traits—and possess a total of 28 specific indicators. Confirmatory analysis of the factors demonstrates a good fit for the five-dimensional model, with each of the dimensions exhibiting high reliability and validity. This scale is innovative in integrating the competency elements with Chinese characteristics, such as commercial acumen, crosscultural mediation skills, and adaptability to the local rule of law. This research not only enriches the competency theory in regard to the field of human resource management but also provides a scientific framework of standards and measurement tools for the selection, training, and evaluation of arbitrators. It thus has significant practical value for enhancing the professionalism and international competitiveness of China's arbitration system.
基金supported by the Scientific Research Program of Hefei Normal University(2024KY71)the Partnership Program of Hefei Normal University(HXXM2022094).
文摘Practical activities are an indispensable piece of science education.As such,assessment of these practical activities is vital for continually enhancing the quality of science instruction.This article presents a tentative framework structured for assessing practical activities in science education.The proposed framework is built upon seven components:engagement and participation,relational thinking,stepwise mastery,contextualization,multidimensional integration,empowerment,and scientific articulacy.The framework might provide science educators with an alternative lens through which to enhance the effectiveness of practical activities,promote student engagement,and better prepare learners for the future.This framework is designed to be additive and complementary to existing assessment approaches and can be adapted and customized to suit specific local contexts and varying grade levels by science educators in the pursuit of excellence in an ever-evolving science education landscape.
文摘The NIST Cybersecurity Framework (NIST CSF) serves as a voluntary guideline aimed at helping organizations, tiny and medium-sized enterprises (SMEs), and critical infrastructure operators, effectively manage cyber risks. Although comprehensive, the complexity of the NIST CSF can be overwhelming, especially for those lacking extensive cybersecurity resources. Current implementation tools often cater to larger companies, neglecting the specific needs of SMEs, which can be vulnerable to cyber threats. To address this gap, our research proposes a user-friendly, open-source web platform designed to simplify the implementation of the NIST CSF. This platform enables organizations to assess their risk exposure and continuously monitor their cybersecurity maturity through tailored recommendations based on their unique profiles. Our methodology includes a literature review of existing tools and standards, followed by a description of the platform’s design and architecture. Initial tests with SMEs in Burkina Faso reveal a concerning cybersecurity maturity level, indicating the urgent need for improved strategies based on our findings. By offering an intuitive interface and cross-platform accessibility, this solution aims to empower organizations to enhance their cybersecurity resilience in an evolving threat landscape. The article concludes with discussions on the practical implications and future enhancements of the tool.
文摘Overall bank performance in a particular year or period is important to all banking industry stakeholders,as it indicates their success or failure relative to predetermined targets.Due to conflicting criteria and uncertainties,assessing bank performance is a complicated decision-making problem.The current paper proposes the Fuzzy Level Based Weight Assessment(F-LBWA),the Fuzzy Logarithm Methodology of Additive Weights(F-LMAW),and the Measurement Alternatives and Ranking according to the Compromise Solution(MARCOS)combination as a practical and robust decisionmaking tool to cope with many complex ambiguities.In the first phase,the suggested hybrid Multi-Criteria Decision-Making(MCDM)approach estimates the weight coefficients of the performance criteria with the aid of a combined version of the F-LBWA and F-LMAW methods.In the second phase,the MARCOS method determines the ranking performance of the decision alternatives.The introduced model is tested and validated on a case study assessing publicly traded bank performance in Pakistan.The findings obtained from the sensitivity analysis revealed that the presented F-LBWAF-LMAW-MARCOS approach produces consistent solutions and is a reliable and effective procedure in rational decision-making.
文摘Proficiency in fundamental movement skills in children is linked to numerous positive physical,behavioral,and cognitive outcomes.The Test of Gross Motor Development is a widely used tool in research to measure this outcome.However,its application faces several limitations and challenges,such as subjectivity in rater judgements,limitation in data precision,and inconsistencies in score aggregations.In this commentary,we discuss these issues and explore how new technology might help address some of the challenges.Nonetheless,a consensus to how scores should be aggregated is still needed,and this could only be achieved through further discussions among researchers in the field.
基金supported by the Yunnan Provincial Education Department Scientific Research Fund Project(Grant No.2022J0525).
文摘Before nationwide implementation of waste classification programs in rural areas,identifying suitable pilot regions is crucial.This study develops a comprehensive framework for assessing and selecting these pilot regions.Data were collected through 654 valid questionnaires and interviews with respondents from rural areas in six provinces across China.Primary assessment criteria included disposal methods for kitchen waste,recyclables,hazardous waste,and residual waste,as well as farmers’willingness to separate hazardous waste when offered compensation and the impact of centralized waste treatment in villages.Secondary criteria focused on disposal methods for agrochemical packages and other hazardous waste.Using the weighted sum of squares method,the study evaluated the suitability of six regions as pilot areas for waste classification.The results identified villages in Jiangsu province and Hebei province as the most suitable pilot regions.Based on the findings,the study provides recommendations to address weaknesses in these regions to enhance the effectiveness of future trials and offers tailored suggestions for other regions to improve their waste classification initiatives.
基金funding provided by University of Natural Resources and Life Sciences Vienna(BOKU).
文摘The increasing frequency and intensity of forest fires,driven by climate change and human activities,pose a significant threat to vital forest ecosystems,particularly where fire is not a natural element in the regeneration cycle.This study aims to identify the indicators influencing forest fire vulnerability and compare maps of forest fire susceptibility that are based on the Intergovernmental Panel on Climate Change tripartite model,with a focus on the vulnerable Hyrcanian forest region in Golestan Province,northern Iran,where forest fires have caused considerable economic losses.On the basis of expert opinions and a literature review,we used geographic information systems,remote sensing and machine learning techniques to select and weigh 30 biophysical,environmental and socioeconomic indicators that affect forest fire vulnerability in the study area.These indicators were rigorously normalized,weighted and amalgamated into a comprehensive forest fire vulnerability index to analyze forest exposure,sensitivity and adaptive capacity.We thus identified and mapped areas with very high forest fire exposure,high sensitivity and low adaptive capacity for urgent targeted intervention and strategic planning to mitigate the impacts of forest fires.The results also revealed a set of critical indicators that contribute more significantly to forest fire vulnerability(e.g.,precipitation,elevation and factors related to biodiversity,human activity and economic reliance on forest resources).Our results provide insights that can inform policy-making,community engagement and environmental management strategies to mitigate the vulnerabilities associated with forest fires in the Hyrcanian forest.
文摘Assessing the vulnerability of a platform is crucial in its design.In fact,the results obtained from vulnerability analyses provide valuable information,leading to precise design choices or corrective solutions that enhance the platform's chances of surviving different scenarios.Such scenarios can involve various types of threats that can affect the platform's survivability.Among such,blast waves impacting the platform's structure represent critical conditions that have not yet been studied in detail.That is,frameworks for vulnerability assessment that can deal with blast loading have not been presented yet.In this context,this work presents a fast-running engineering tool that can quantify the risk that a structure fails when it is subjected to blast loading from the detonation of high explosive-driven threats detonating at various distances from the structure itself.The tool has been implemented in an in-house software that calculates vulnerability to various impacting objects,and its capabilities have been shown through a simplified,yet realistic,case study.The novelty of this research lies in the development of an integrated computational environment capable of calculating the platform's vulnerability to blast waves,without the need for running expensive finite element simulations.In fact,the proposed tool is fully based on analytical models integrated with a probabilistic approach for vulnerability calculation.
文摘This study aims to assess seismic hazards and develop effective mitigation strategies for the Mentawai-Siberut region in Indonesia.The research uses quantitative and qualitative methods to analyze historical seismic data,predictive models,and stakeholder perspectives.The quantitative analysis includes seismic hazard estimation using the Gutenberg-Richter formula,ground movement analysis based on GMPE,and time interval calculations to forecast future earthquakes.Qualitative methods involve Policy Network Theory to explore the roles and interactions of various stakeholders in disaster management,including government agencies,Indonesian Archipelago Youth Association(NGOs),local communities,and academic researchers.Findings reveal significant seismic activity in the area,with historical earthquakes of magnitudes 8 and 9 occurring at intervals of 18 to 232 years.Predictions suggest a potential magnitude 8 earthquake around 2083,with a megathrust event likely around 2123.The study also identifies economic costs and losses,with damage from a megathrust estimated between USD 1.5–2.5 billion and 10-20 billion,including destroyed homes and displaced populations.Challenges include infrastructure limitations,logistical constraints,and enhancing disaster preparedness and response.The study emphasizes the importance of improving infrastructure,strengthening disaster preparedness,and updating early warning systems.Effective collaboration among stakeholders and integrating local knowledge into disaster management strategies are crucial for enhancing regional resilience.Recommendations include completing infrastructure projects like the Trans-Mentawai Road,increasing community engagement,and utilizing scientific data for evidence-based policymaking.Addressing these recommendations and limitations is essential for developing a robust disaster management framework to mitigate regional seismic risks.
基金financial supported by National Natural Science Foundation of China (42104010, 42174097, 41974093, and 41774088)the Fundamental Research Funds for the Central Universities
文摘Changes in lake levels, as an indicator of climate change, are crucial for understanding water resources.Satellite altimetry has proven to be an effective technique for monitoring water level changes in inland lakes. However, high-altitude and high-latitude lakes undergo seasonal freezing and melting, affecting satellite altimetry accuracy. This paper evaluates the accuracy of lake level height observations by the CryoSat-2, which uses synthetic aperture radar(SAR) across seasons. First, we used lake boundary based on optical remote sensing data to extract the footprints of CryoSat-2 that fall on Namco and Zhari Namco.After elevation conversion and anomaly identification, we obtained the time series of lake levels. These data were compared and verified against lake levels from in-situ measurements to assess the accuracy of CryoSat-2. The results show that CryoSat-2 can monitor lake level height with an accuracy of about 10-13 cm. The correlation coefficient between CryoSat-2 observations and in-situ measurements over Namco is 0.80(p < 0.01), with a Root Mean Square Error(RMSE) of 13 cm. For Zhari Namco, the correlation coefficient is 0.91, with an RMSE of 10 cm, indicating a better match. At the seasonal scale, the seasonal correlation coefficients between CryoSat-2 and in-situ measurement in Namco are 0.47(spring),0.79(summer), and 0.91(fall) with no observations available for winter. The lower correlation in spring may be due to incomplete ice melting. For Zhari Namco, the seasonal correlation coefficients are 0.89(spring), 0.93(summer), 0.89(fall), and 0.87(winter). The results show that CryoSat-2 accuracy is higher in summer and fall, while slightly lower in spring and winter, indicating that ice formation affects accuracy. Even during winter, the altimetry results do not significantly exceed the in-situ lake water level observations.
基金supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Republic of Korea(NRF-2021S1A3A2A02096338).
文摘Background:In this study,we aimed to validate and test the reliability of the Yonsei lifestyle profile(YLP)in assessing multifaceted health lifestyle levels in a study population from the United States.Methods:The YLP-English version and health-promoting lifestyle profile II were administered to 100 individuals living in the United States.Concurrent validity was analyzed using Pearson's correlation coefficient,and discriminant validity was examined by comparing sex and age differences through t-tests and multiple variance analysis.Internal consistency was assessed using Cronbach'sαfor each sub-factor.Results:The YLP-English Version demonstrated concurrent validity with the Health-Promoting Lifestyle Profile II,showing consistent correlations for the total score(0.3,p<0.01)and frequency sub-factors(0.25-0.69,p<0.01).Among the satisfaction sub-factors,only nutrition showed a weak negative correlation(-0.19,p<0.01);all others were nonsignificant.Discriminant validity revealed no significant sex differences,but physical activity frequency varied across age groups.Internal consistency was high(Cronbach'sα=0.80-0.86).Conclusion:In this study,we validated the YLP-English version as a reliable instrument for assessing health-related lifestyle behaviors.The YLP uniquely captures both lifestyle frequency and satisfaction,offering a comprehensive perspective on health behaviors.Although this tool is currently most applicable in population-level studies,future research should establish clinical thresholds to enhance its utility in individualized health assessments and interventions.
文摘The concentration of development projects near protected areas can undermine their conservation objectives.This study examines the impact of such projects on wildlife abundance in Campo-Ma’an National Park(CMNP).Information from the CMNP Conservation Department was analysed to investigate the link between development projects around the park and changes in wildlife populations,and analysis was conducted using statistical tools,including Excel 2020 and SPSS.Pearson’s correlation coefficient was employed to assess the relationship between wildlife abundance indicators and the number of development projects surrounding the park.The findings reveal a significant decline in the abundance of key species,including elephants,great apes(such as gorillas and chimpanzees),and mandrills,over the past decade.Although a brief period of improvement was observed in the early 2010s,these gains were quickly reversed.Overall,the pattern shows that as development activities increased,wildlife numbers tended to decrease.These results underscore the urgent need for stricter regulation of development near the park and for comprehensive environmental and social impact assessments to be conducted before projects commencement.This process must receive greater attention from authorities and stakeholders to regulate activities around national parks and foster conservation efforts.Strengthening this oversight will help to maintain the park’s ecological integrity and promote sustainable conservation.
基金supported by grants from Singhealth Duke-NUS Academic Medicine Research grant(AM/SU035/2020)NMRC Clinician-Scientist Individual Research Grant New Investigator Grant(CNIG20nov-0003).
文摘Chemical exposure during prenatal development has significant implications for both maternal and child health.Compared to blood,saliva is a non-invasive and less resource-intensive,alternative.Given the temporal variability of xenobiotic metabolites(XM),repeated sampling is essential.Therefore,saliva offers a valuable tool for the longitudinal assessment of prenatal exposomes.Despite its potential,no studies have explored saliva for XM measurement.This study pioneered using saliva to assess XM detectability and investigate the associations between prenatal XM and endogenous metabolomes in pregnant women.Saliva samples were analysed using mass spectrometry from 80 pregnant women at 24–34 weeks gestation.Metabolomes and exposomes were annotated using the Human Metabolome and U.S.Environmental Protection Agency databases.Metabolome-XM associations were clustered using Glay community clustering.Linear regression models,adjusted for age,estimated associations between catecholamines and XMs.XM levels were validated in a cohort of women(n=14)with and without preeclampsia.Our study identified 582 metabolomes and 125 XM in saliva,demonstrating its potential as a matrix for exposure measurement.After false discovery rate correction,18109 significant metabolome-XM associations were identified.Community clustering revealed 37 connected clusters,with the largest cluster(238 nodes)enriched in tyrosine and catecholamine metabolism.Food-contactchemicals and food-additives were significantly associated with higher catecholamine and their metabolite levels.Subgroup analyses revealed higher concentrations of these chemicals in women with preeclampsia compared to healthy controls.This study demonstrates that saliva contains valuable molecular data for measuring exposomes.Food-related chemicals were associated with higher catecholamine levels,which may be relevant to the prevalence of hypertensive crises in pregnancy.
文摘Chronic diseases,or NCDs(noncommunicable diseases),constitute a major global health challenge,causing millions of deaths and imposing substantial economic burdens annually.This paper introduces the Health Score,a comprehensive framework for assessing chronic disease risk by integrating diverse determinants of health,including social,economic,environmental,behavioral,treatment,culture,and nature factors.The Health Score,ranging from 0 to 850,quantifies indivi dual and population-level health risks while identifying protective factors through a structured methodology that supports targeted interventions at individual,corporate,and community scales.The paper highlights the rising prevalence of chronic diseases in the United States,projecting that nearly half of the population will be affected by 2030,alongside a global economic burden expected to reach trillions of dollars.Existing surveillance tools,such as the CDS(Chronic Disease Score)and CDIs(Chronic Disease Indicators),are examined for their roles in monitoring health disparities.The Health Score advances a holistic,proactive approach,emphasizing lifestyle modifications,equitable healthcare access,economic opportunities,social support,nature exposure,cu ltural awareness,and community engagement.By elucidating the complex interplay of health determinants,this framework equips stakeholders with actionable insights to implement effective prevention strategies,ultimately fostering healthier,more resi lient populations.
基金the financial support from the National Natural Science Foundation of China (U22B20148,22208143,and 22278204)the International Science and Technology Cooperation Project of the Innovative Supporting Plan from the Jiangsu Provincial Department of Science and Technology (BZ2022040)+1 种基金the State Key Laboratory of Materials-Oriented Chemical Engineering (ZK202101,SKL-MCE-24A09,and the Open Project SKL-MCE-23B)support from the China National Petroleum Corporation。
文摘Excessive fossil fuel use has increased carbon dioxide(CO_(2)) emissions,driving climate change and ocean acidification.This review evaluates the potential of higher alcohols as fuels for carbon circularity,comparing their properties,energy efficiency,and technology readiness with hydrogen,methane,and methanol.Higher alcohols,produced via CO_(2) hydrogenation,exhibit advantages such as liquid-phase storage,higher energy density,and safer handling.Additionally,their clean combustion produces fewer pollutants like CO and NO_(x).However,CO_(2) hydrogenation to higher alcohols faces challenges,including high energy demands,kinetic barriers,and immature production technologies,resulting in lower energy efficiency compared to H_(2),methane,and methanol.Higher alcohols,with their superior energy density and safety,hold promise as sustainable fuels,particularly when integrated with CO_(2) capture technologies.However,improvements in catalyst performance,process integration,and production scalability are critical for their widespread adoption.
基金supported by the National Research Foundation,Singapore,funded under Energy Research Testbed and Industry Partnership Funding Initiative,part of the Energy Grid(EG)2.0 programme.
文摘Rapid developments in the electronic information industry drive the increased energy usage and carbon emission of data center buildings,prompting the focus on the energy efficiency and environmental sustainability.Expanded operation envelopes of tropical data centers is assessed to analyze the potential for the building energy savings and carbon emission reduction through collaborative analysis of operation modes(OMs),supply air temperature(SAT),and outdoor air temperature(OAT).The OMs of compression vary with the setpoints of SAT,in which the average exergy efficiency of compressors at alternate operation mode is 6.8%and 8.0%lower than that of double and single compression operations.As SAT rises from 20℃to 32℃,the system exergoeconomic factor increases from 5.4%to 8.0%,and the average carbon cost decreases by 36.5%.Additionally,with just an 8.5%increase in exergy cost(i.e.,Case 8)at OAT rising from 30 to 34℃,the high SAT and low refrigerant charges provide considerable exergy cost advantages versus resisting the OAT fluctuations.Dynamic operation strategies are also proposed and compared to cope with the impacts of tropical environments.Compared to the 26℃SAT baseline,the average energy savings are 9.1-14.7%,indicating the ability to fully utilize outdoor and indoor conditions.
基金financial support from the National Institute of Natural Hazards,Ministry of Emergency Management of China(Grant No.ZDJ2021-12)。
文摘The assessment of landslide susceptibility triggered by earthquakes serves as a fundamental basis for effective emergency response and post-disaster reconstruction efforts.However,current predictive models often face limitations in accuracy,with the prediction rates of most models ranging from 80%to 90%.This study introduces a new hybrid machine learning framework,termed the Subtractive Clustering Method-based Adaptive Neural Network Fuzzy Inference System(SCM-ANFIS),and evaluates its performance in the Wenchuan earthquake region.This region features distinctive geology(e.g.,Longmenshan Fault-governed complex tectonics)and abundant fundamental data;additionally,the 2008 Wenchuan Earthquake provides a pertinent case for earthquakeinduced landslide model evaluation.Based on a literature review and correlation analysis,this study systematically identified 12 key influencing factors that collectively characterize the region's high landslide susceptibility,shaped by intense seismic activity,complex terrain,and fragmented rock masses.Positive and negative samples were extracted as target variables through buffer sampling to calculate earthquake-induced landslide susceptibility.The susceptibility zoning map was then calibrated and generated by incorporating the regional landslide area percentage.The study concludes the following:(1)Compared to traditional machine learning approaches,the model demonstrates strong performance and stability,achieving a prediction accuracy of 98.5%.Approximately 97.89%of historically documented landslides in the Wenchuan region were located within areas identified as having high susceptibility,which aligns well with observed spatial distributions.(2)Increase in the buffer distance contributes to enhance prediction accuracy while a larger sample size improves model stability.(3)The model exhibits superior performance and possesses scalability for application in other regions,such as Jiuzhaigou and Luding.(4)Nonetheless,limitations remain regarding uncertainty,sample composition,algorithmic design,and practical implementation.Future research should focus on improving data precision and optimizing algorithmic frameworks.Overall,this study provides valuable support for landslide susceptibility assessments and contributes essential data for disaster risk mitigation efforts.
文摘Eco-driving behaviors have been recommended around the world because the transport is a key factor of energy use and pollution emissions.Therefore,based on the driving decision model,this paper introduces three aspects of the driving decisions(strategic decision,tactical decision and operation decision)to analyze the economy of vehicle energy.The analytic hierarchy process(AHP)is used to assign the weight of the internal evaluation indexes,so as to form a complete assessment for drivers'eco-driving behaviors.The research result can not only quantitatively describe the energy-saving effect of drivers'decisions,but also put forward targeted driving suggestions to optimize drivers'eco-driving behaviors.This assessment model helps to clarify the potential of eco-driving on energy economy of transportation in a hierarchical way,and provides a valuable theoretical basis for the further promotion and application of eco-driving education.
基金funded in part by the Fundamental Research Funds for the Central Universities under Grant NS2023052in part by the Natural Science Foundation of Jiangsu Province of China under Grants No.BK20231439 and No.BK20222012.
文摘With the expanding applications of unmanned aerial vehicles(UAVs),precise flight evaluation has emerged as a critical enabler for efficient path planning,directly impacting operational performance and safety.Traditional path planning algorithms typically combine Dubins curves with local optimization to minimize trajectory length under 3D spatial constraints.However,these methods often overlook the correlation between pilot control quality and UAV flight dynamics,limiting their adaptability in complex scenarios.In this paper,we propose an intelligent flight evaluation model specifically designed to enhancemulti-waypoint trajectory optimization algorithms.Our model leverages a decision tree to integrate attitude parameters and trajectory matching metrics,establishing a quantitative link between pilot control quality and UAV flight states.Experimental results demonstrate that the proposed model not only accurately assesses pilot performance across diverse skill levels but also improves the optimality of generated trajectories.When integrated with our path planning algorithm,it efficiently produces optimal trajectories while strictly adhering to UAV flight constraints.This integrated framework highlights significant potential for real-time UAV training,performance assessment,and adaptive mission planning applications.
基金supported by the Beijing Nova Program (20230484277)the National Natural Science Foundation of China (82303955)。
文摘Dear Editor,On July 25,2024,an Oncologic Drugs Advisory Committee meeting was held to discuss the design of the AEGEAN trial,which evaluated the perioperative use of durvalumab for resectable non-small cell lung cancer(NSCLC)[1].The Food and Drug Administration(FDA)stated that the two-arm trial was not designed to isolate contributions of neoadjuvant and adjuvant phases.Since the clinical benefit of adjuvant durvalumab remains uncertain,this limitation raises concerns about potential over-treatment.
